With the development of social networks, various forum communities appear. A group of users having similar interest may gather in a same forum community and discuss various recent popular topics in various sections of the forum. In a forum, the most fundamental objectives of a user are to read content and acquire information. Therefore, to provide the user with more content or information, when the user is reading content, contents of related subjects may be automatically recommended to the user. It is convenient for the user to acquire relate information, and to improve the stickiness of the website and a click-through rate of a website.
An existing content recommendation method is based on browsing behavior of a user. In the method, it is assumed that users browse the same content have the same interest, browsing behavior of users in a forum is analyzed to establish a two-dimensional matrix for user and browsing-content, a degree of correlation between contents is calculated based on this matrix by using an algorithm such as coordinated filtering, to obtain a recommendation result, and to recommend the recommendation result to a user.
However, existing technologies at least have the following problems. In one forum, a same user may be interested in various aspects, and browsing behavior of the user may cover contents of different subjects. A simple assumption that users that browse the same content have the same interest in existing technologies results in that contents of different subjects are regarded to be close subjects. A recommendation result obtained in this way is not necessarily the content that a user is interested in, which reduces accuracy of recommended content compared with the content that the user is interested in.
In addition, when a forum has a relatively small amount of data, and a user also has a relatively small amount of browsing behavior data, the two-dimensional matrix of user and browsing content may become relatively scarce, which severely affects a final recommendation effect. Therefore, a recommendation result that is purely obtained from browsing behavior of a user is not necessarily accurate for the user, and therefore accuracy of a recommendation result from a forum community to a user is affected.
Therefore, there is a need to solve technical problems in the Internet and computer technology to improve accuracy for recommending contents or information to a user in a forum.